Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes

Multi-frame depth estimation generally achieves high accuracy relying on the multi-view geometric consistency. When applied in dynamic scenes, e.g., autonomous driving, this consistency is usually violated in the dynamic areas, leading to corrupted estimations. Many multi-frame methods handle dynamic areas by identifying them with explicit masks and compensating the multi-view cues with monocular cues represented as local monocular depth or features. The improvements are limited due to the uncontrolled quality of the masks and the underutilized benefits of the fusion of the two types of cues. In this paper, we propose a novel method to learn to fuse the multi-view and monocular cues encoded as volumes without needing the heuristically crafted masks. As unveiled in our analyses, the multi-view cues capture more accurate geometric information in static areas, and the monocular cues capture more useful contexts in dynamic areas. To let the geometric perception learned from multi-view cues in static areas propagate to the monocular representation in dynamic areas and let monocular cues enhance the representation of multi-view cost volume, we propose a cross-cue fusion (CCF) module, which includes the cross-cue attention (CCA) to encode the spatially non-local relative intra-relations from each source to enhance the representation of the other. Experiments on real-world datasets prove the significant effectiveness and generalization ability of the proposed method.Comment: Accepted by CVPR 2023. Code and models are available at: https://github.com/ruili3/dynamic-multiframe-dept

Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers

Prompt tuning attempts to update few task-specific parameters in pre-trained models. It has achieved comparable performance to fine-tuning of the full parameter set on both language understanding and generation tasks. In this work, we study the problem of prompt tuning for neural text retrievers. We introduce parameter-efficient prompt tuning for text retrieval across in-domain, cross-domain, and cross-topic settings. Through an extensive analysis, we show that the strategy can mitigate the two issues -- parameter-inefficiency and weak generalizability -- faced by fine-tuning based retrieval methods. Notably, it can significantly improve the out-of-domain zero-shot generalization of the retrieval models. By updating only 0.1% of the model parameters, the prompt tuning strategy can help retrieval models achieve better generalization performance than traditional methods in which all parameters are updated. Finally, to facilitate research on retrievers' cross-topic generalizability, we curate and release an academic retrieval dataset with 18K query-results pairs in 87 topics, making it the largest topic-specific one to date

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

A Comparative Study on Register Based on Chinese and International Studies: A Scientometric Analysis in CiteSpace (2010-2021)

This paper conducts a comprehensive review and comparative analysis of the research on register published in Chinese and international authoritative journals from 2010 to 2021 by employing CiteSpace 5.8.R3, a visual bibliometric software. It describes the number of publications, the keywords with the strongest citation bursts, research institutions, journals and influential authors, and pinpoints the principal frontiers of register. The results indicate that the number of publications of Chinese register research has shown a significant downward trend on the whole, while international register research has shown a significant upward trend on the whole. The journal of high-cited papers on register studies in China has a low impact factor, while international hot papers on register studies have a high impact factor. Chinese scholars focus on the different research perspectives of the register (systemic functional linguistics, multidimensional analysis and corpus), while international research pays attention to register variation, especially English variation and Spanish variation, and register in academic writing. Influential scholars leading the trend of register research include Biber and Rooy. The findings of this study would provide some academic and pedagogical implications on the register for Chinese scholars

Effect of SiC Content on the Ablation and Oxidation Behavior of ZrB2-Based Ultra High Temperature Ceramic Composites

material

Preparation and characterization of high-performance ZrB2–SiC–Cf composites sintered at 1450 °C

Abstract ZrB2–SiC–Cf composites containing 20–50 vol% short carbon fibers were hot pressed at low sintering temperature (1450 °C) using nanosized ZrB2 powders, in which the fiber degradation was effectively inhibited. The strain-to-failure values of such composites increased with increasing fiber content, and the value for the composite with 50 vol% Cf was even more than 3 times higher than that of the composite with 20 vol% Cf. Furthermore, the composite exhibited non-brittle fracture mode when the fiber content was above 30 vol%, and the thermal shock critical temperature difference of the composite with 30 vol% Cf was up to 727 °C, revealing excellent thermal shock resistance of this composite. Additionally, ZrB2–SiC–Cf composites displayed good oxidation resistance when the fiber content was below 40 vol%, suggesting that this method provides a promising way for preparation of high-performance ZrB2–SiC–Cf composites at low temperature

Effects of Sous Vide Cooking on the Physicochemical and Volatile Flavor Properties of Half-Shell Scallop (<i>Chlamys farreri</i>) during Chilled Storage

This study explored the effects of sous vide (SV) cooking treatments on the physicochemical quality and volatile flavor of half-shell scallop (Chlamys farreri) during 30 d of chilled storage. The vacuum-packed scallop samples were cooked at 70 °C (SV-70) and 75 °C (SV-75) and maintained for 30 min. The samples were compared with the positive control (cooked at 100 °C for 10 min, CK). The results indicate that the total volatile basic nitrogen (TVBN), pH, texture, and malondialdehyde (MDA) content gradually increased, while the myofibrillar protein (MP) extraction rate of the CK, SV-70, and SV-75 samples significantly decreased with increasing chilled storage time. Significantly, the SV cooking treatments maintained a much higher water-holding capacity of scallop muscle, compared with the conventional cooking process at 100 °C. Additionally, the SV-75 cooking treatment maintained relatively stable TVBN, pH, and MDA content, springiness, and shearing force properties of scallop samples, especially during 0–20 d of storage. Volatile flavor analysis showed that a total of 42 volatile organic compounds (VOCs) were detected in the scallop samples, and there were no considerable differences in these VOCs between the CK and SV-75 cooked samples (0 d). Overall, the SV cooking treatments effectively maintained acceptable and stable physicochemical and volatile flavor properties of half-shell scallop samples during chilled storage

A mixed human body modeling method based on 3D body scanning for clothing industry

Purpose The purpose of this paper is to propose a relatively simple and rapid method to create a digital human model (DHM) to serve clothing industry. Design/methodology/approach Human body’s point cloud is divided into hands, foots, head and torso. Then forward modeling method is used to model hands and foots, photo modeling method is used to model head and reverse modeling method is used to model torso. After that, hands, foots, head and torso are integrated together to get a static avatar. Next, virtual skeleton is bound to the avatar. Finally, a lifelike digital human body model is created by the mixed modeling method (MMM). Findings In allusion to the defect of the three-dimension original data of human body, this paper presented an MMM, with which we can get a realistic digital human body model with accurate body dimensions. The DHM can well meet the needs of fashion industry. Practical implications The DHM, which is got by the MMM, can be well applied in the field of virtual try on, virtual fashion design, virtual fashion show and so on. Originality/value The originality of the paper lies in the integration of forward modeling, reverse modeling and photo modeling to present a novel method of human body modeling